Empiricism and stochastics in cellular automaton modeling of urban land use dynamics

An increasing number of models for predicting land use change in regions of rapidurbanization are being proposed and built using ideas from cellular automata (CA)theory. Calibrating such models to real situations is highly problematic and to date,serious attention has not been focused on the estimation problem. In this paper, wepropose a structure for simulating urban change based on estimating land usetransitions using elementary probabilistic methods which draw their inspiration fromBayes' theory and the related ?weights of evidence? approach. These land use changeprobabilities drive a CA model ? DINAMICA ? conceived at the Center for RemoteSensing of the Federal University of Minas Gerais (CSR-UFMG). This is based on aneight cell Moore neighborhood approach implemented through empirical land useallocation algorithms. The model framework has been applied to a medium-size townin the west of São Paulo State, Bauru. We show how various socio-economic andinfrastructural factors can be combined using the weights of evidence approach whichenables us to predict the probability of changes between land use types in differentcells of the system. Different predictions for the town during the period 1979-1988were generated, and statistical validation was then conducted using a multipleresolution fitting procedure. These modeling experiments support the essential logicof adopting Bayesian empirical methods which synthesize various information aboutspatial infrastructure as the driver of urban land use change. This indicates therelevance of the approach for generating forecasts of growth for Brazilian citiesparticularly and for world-wide cities in general

Tracer Dispersion in a Self-Organized Critical System

We have studied experimentally transport properties in a slowly driven granular system which recently was shown to display self-organized criticality [Frette {\em et al., Nature} {\bf 379}, 49 (1996)]. Tracer particles were added to a pile and their transit times measured. The distribution of transit times is a constant with a crossover to a decaying power law. The average transport velocity decreases with system size. This is due to an increase in the active zone depth with system size. The relaxation processes generate coherently moving regions of grains mixed with convection. This picture is supported by considering transport in a $1D$ cellular automaton modeling the experiment.Comment: 4 pages, RevTex, 1 Encapsulated PostScript and 4 PostScript available upon request, Submitted to Phys. Rev. Let

Effects of Process Variables and Size Scale on Solidification Microstructure in Laser-Based Solid Freeform Fabrication of Ti-6Al-4V

Mechanical Engineerin

CellLab-CTS 2015: continuous-time stochastic cellular automaton modeling using Landlab

CellLab-CTS 2015 is a Python-language software library for creating two-dimensional, continuous-time stochastic (CTS) cellular automaton models. The model domain consists of a set of grid nodes, with each node assigned an integer state code that represents its condition or composition. Adjacent pairs of nodes may undergo transitions to different states, according to a user-defined average transition rate. A model is created by writing a Python code that defines the possible states, the transitions, and the rates of those transitions. The code instantiates, initializes, and runs one of four object classes that represent different types of CTS models. CellLab-CTS provides the option of using either square or hexagonal grid cells. The software provides the ability to treat particular grid-node states as moving particles, and to track their position over time. Grid nodes may also be assigned user-defined properties, which the user can update after each transition through the use of a callback function. As a component of the Landlab modeling framework, CellLab-CTS models take advantage of a suite of Landlab's tools and capabilities, such as support for standardized input and output

Two-dimensional cellular automaton model of traffic flow with open boundaries

A two-dimensional cellular automaton model of traffic flow with open boundaries are investigated by computer simulations. The outflow of cars from the system and the average velocity are investigated. The time sequences of the outflow and average velocity have flicker noises in a jamming phase. The low density behavior are discussed with simple jam-free approximation.Comment: 14 pages, Phys. Rev. E in press, PostScript figures available at ftp://hirose.ai.is.saga-u.ac.jp/pub/documents/papers/1996/2DTR/ OpenBoundaries/Figs.tar.g